Optimization of Low-Cost Data Acquisition Equipment Applied to Bearing Condition Monitoring

César Ricardo Soto-Ocampo (), Joaquín Maroto, Juan David Cano-Moreno and José Manuel Mera
Additional contact information
César Ricardo Soto-Ocampo: Railway Technology Research Center (Centro de Investigación en Tecnología Ferroviaria-CITEF), Mechanical Engineering Department, Universidad Politécnica de Madrid, 2 José Gutiérrez Abascal Street, 28006 Madrid, Spain
Joaquín Maroto: Railway Technology Research Center (Centro de Investigación en Tecnología Ferroviaria-CITEF), Mechanical Engineering Department, Universidad Politécnica de Madrid, 2 José Gutiérrez Abascal Street, 28006 Madrid, Spain
Juan David Cano-Moreno: Escuela Técnica Superior de Ingeniería y Diseño Industrial, Universidad Politécnica de Madrid, 28012 Madrid, Spain
José Manuel Mera: Railway Technology Research Center (Centro de Investigación en Tecnología Ferroviaria-CITEF), Mechanical Engineering Department, Universidad Politécnica de Madrid, 2 José Gutiérrez Abascal Street, 28006 Madrid, Spain

Mathematics, 2023, vol. 11, issue 16, 1-21

Abstract: The development of low-cost data acquisition equipment is relevant in the increasingly automated industry of today. This study presents the optimization of low-cost data acquisition equipment performance to achieve acquisition speeds of 200 kHz. This was possible by evaluating two essential aspects: considering the influence of the power supplied by the power source and changing the type of data used from “Double” to “uint”. This equipment was validated through the acquisition of known waves and vibration signals from a bearing test bench. The frequency component was satisfactorily identified in each case, for both the known waves and the damaged bearing components. This demonstrated the viability of developing low-cost data acquisition equipment that can be implemented to monitor bearing condition.

Keywords: data acquisition systems; condition monitoring; bearing diagnostics; vibration analysis; Raspberry Pi (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/11/16/3498/pdf (application/pdf)
https://www.mdpi.com/2227-7390/11/16/3498/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:11:y:2023:i:16:p:3498-:d:1216347

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().